← Authors

Rajiv Khanna

25 papers · 2014–2026 · 8 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (13) 🧭 Keyword Pioneer 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (10) 🐝 Cross-Pollinator (14) πŸ† Keyword Champion (2) πŸ† Grand Slam πŸ”₯ Unstoppable (11) πŸ’Ž Century Club (24) πŸ—ƒοΈ Keyword Collector (114) πŸ“ˆ Trend Setter ⚑ Prolific Year (5)

Conferences

AISTATS (9) NIPS (7) ICLR (2) ICML (2) UAI (2) AAAI (1) COLT (1) IJCAI (1)

Top co-authors

Michael W. Mahoney (7) Joydeep Ghosh (7) Anastasios Kyrillidis (3) Liam Hodgkinson (3) Oluwasanmi O Koyejo (3) Francesco Locatello (3) Sanmi Koyejo (2) Oluwasanmi Koyejo (2) Russell Poldrack (2) Kannan Ramchandran (2)

Research topics

Statistics (1)

Keywords

submodular optimization (4) greedy algorithm (3) feature selection (3) bayesian inference (3) kernel methods (3) approximate inference (2) column subset selection (2) iterative hard thresholding (2) greedy optimization (2) bayesian quadrature (2) generalization bound (2) information projection (2) spectral analysis (2) low-rank approximation (2) sparse optimization (2) nystrom method (2) variational inference (2) convergence analysis (2) fisher kernel (1) decision making (1)

Papers

Align When They Want, Complement When They Need! Human-Centered Ensembles for Adaptive Human-AI Collaboration AAAI 2026
The Space Complexity of Approximating Logistic Loss NIPS 2024
A Precise Characterization of SGD Stability Using Loss Surface Geometry ICLR 2024
Generalization Guarantees via Algorithm-dependent Rademacher Complexity COLT 2023
Fast Feature Selection with Fairness Constraints AISTATS 2023
Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers ICML 2022
Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective AISTATS 2021
Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification ICLR 2021
Geometric rates of convergence for kernel-based sampling algorithms UAI 2021
LocalNewton: Reducing communication rounds for distributed learning UAI 2021
Improved Guarantees and a Multiple-descent Curve for Column Subset Selection and the Nystrom Method (Extended Abstract) IJCAI 2021
Boundary thickness and robustness in learning models NIPS 2020
Improved guarantees and a multiple-descent curve for Column Subset Selection and the Nystrom method NIPS 2020
Interpreting Black Box Predictions using Fisher Kernels AISTATS 2019
Learning Sparse Distributions using Iterative Hard Thresholding NIPS 2019
Boosting Variational Inference: an Optimization Perspective AISTATS 2018
Boosting Black Box Variational Inference NIPS 2018
IHT dies hard: Provable accelerated Iterative Hard Thresholding AISTATS 2018
Information Projection and Approximate Inference for Structured Sparse Variables AISTATS 2017
On Approximation Guarantees for Greedy Low Rank Optimization ICML 2017
Scalable Greedy Feature Selection via Weak Submodularity AISTATS 2017
A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe AISTATS 2017
Examples are not enough, learn to criticize! Criticism for Interpretability NIPS 2016
Sparse Submodular Probabilistic PCA AISTATS 2015
On Prior Distributions and Approximate Inference for Structured Variables NIPS 2014